Experiments

Exhibition Experiments is a lively collection that considers experiments with museological form that challenge our understanding of – and experience with – museums. Explores examples of museum experimentalism in light of cutting-edge museum theory Draws on a range of global and topical examples, including museum experimentation, exhibitionary forms, the fate of conventional notions of ‘object’ and ‘representation’, and the impact of these changes Brings together an international group of art historians, anthropologists, and sociologists to question traditional disciplinary boundaries Considers the impact of technology on the museum space tackles a range of examples of experimentalism from many different countries, including Australia, Austria, Germany, Israel, Luxembourg, Sweden, the UK and the US Examines the changes and challenging new possibilities facing museum studies

The most comprehensive, single-volume guide to conducting experiments with mixtures «If one is involved, or heavily interested, in experiments on mixtures of ingredients, one must obtain this book. It is, as was the first edition, the definitive work.» -Short Book Reviews (Publication of the International Statistical Institute) «The text contains many examples with worked solutions and with its extensive coverage of the subject matter will prove invaluable to those in the industrial and educational sectors whose work involves the design and analysis of mixture experiments.» -Journal of the Royal Statistical Society «The author has done a great job in presenting the vital information on experiments with mixtures in a lucid and readable style. . . . A very informative, interesting, and useful book on an important statistical topic.» -Zentralblatt fur Mathematik und Ihre Grenzgebiete Experiments with Mixtures shows researchers and students how to design and set up mixture experiments, then analyze the data and draw inferences from the results. Virtually every technique that has appeared in the literature of mixtures can be found here, and computing formulas for each method are provided with completely worked examples. Almost all of the numerical examples are taken from real experiments. Coverage begins with Scheffe lattice designs, introducing the use of independent variables, and ends with the most current methods. New material includes: * Multiple response cases * Residuals and least-squares estimates * Categories of components: Mixtures of mixtures * Fixed as well as variable values for the major component proportions * Leverage and the Hat Matrix * Fitting a slack-variable model * Estimating components of variances in a mixed model using ANOVA table entries * Clarification of blocking mates and choice of mates * Optimizing several responses simultaneously * Biplots for multiple responses

A unique text that simplifies experimental business design and is dedicated to the R language  Business Experiments with R  offers a guide and explores the fundamentals of experiment business designs. The book fills a gap in the literature with its discussion of business statistics, addressing issues such as small samples, lack of normality, and data confounding. The author—a noted expert on the topic—puts the focus on the A/B tests (and their variants) that are widely used in industry but not typically covered in business statistics textbooks.  The text contains the tools needed to design and analyze two-treatment experiments (i.e., A/B tests) to answer business questions. The author highlights the strategic and technical issues involved in designing experiments that will truly affect organizations. The book then builds on the foundation laid in Part I and expands on multivariable testing. Today’s companies use experiments to solve a broad range of problems, and  Business Experiments with R  is an essential resource for any business student. This important text:  Presents the key ideas that business students need to know about experiments Offers a series of examples, focusing on specific business questions Helps develop the ability to frame ill-defined problems and determine what data and types of analysis provide information about each problem Contains supplementary material, such as data sets available to everyone and an instructor-only companion site featuring lecture slides and an answer key Written for students of general business, marketing, and business analytics,  Business Experiments with R  is an important text that helps to answer business questions by highlighting the strategic and technical issues involved in designing experiments that will truly affect organizations.

Comprehensively covers the fundamental scientific principles and technologies that are used in the design of modern computer-controlled machines and processes. Covers embedded microcontroller based design of machines Includes MATLAB®/Simulink®-based embedded control software development Considers electrohydraulic motion control systems, with extensive applications in construction equipment industry Discusses electric motion control, servo systems, and coordinated multi-axis automated motion control for factory automation applications Accompanied by a website hosting a solution manual

Adopting a groundbreaking approach, the highly regarded author shows how to design methods for planning increasingly complex experiments. He begins with a brief introduction to standard quality methods and the technology in standard electric circuits. The book then gives numerous examples of how to apply the proposed methodology in a series of real-life case studies. Although these case studies are taken from the printed circuit board industry, the methods are equally applicable to other fields of engineering.

A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

Covers experiment planning, execution, analysis, and reporting This single-source resource guides readers in planning and conducting credible experiments for engineering, science, industrial processes, agriculture, and business. The text takes experimenters all the way through conducting a high-impact experiment, from initial conception, through execution of the experiment, to a defensible final report. It prepares the reader to anticipate the choices faced during each stage.  Filled with real-world examples from engineering science and industry, Planning and Executing Credible Experiments: A Guidebook for Engineering, Science, Industrial Processes, Agriculture, and Business offers chapters that challenge experimenters at each stage of planning and execution and emphasizes uncertainty analysis as a design tool in addition to its role for reporting results. Tested over decades at Stanford University and internationally, the text employs two powerful, free, open-source software tools: GOSSET to optimize experiment design, and R for statistical computing and graphics. A website accompanies the text, providing additional resources and software downloads. A comprehensive guide to experiment planning, execution, and analysis Leads from initial conception, through the experiment’s launch, to final report Prepares the reader to anticipate the choices faced throughout an experiment Hones the motivating question Employs principles and techniques from Design of Experiments (DoE) Selects experiment designs to obtain the most information from fewer experimental runs Offers chapters that propose questions that an experimenter will need to ask and answer during each stage of planning and execution Demonstrates how uncertainty analysis guides and strengthens each stage Includes examples from real-life industrial experiments Accompanied by a website hosting open-source software Planning and Executing Credible Experiments is an excellent resource for graduates and senior undergraduates—as well as professionals—across a wide variety of engineering disciplines.

The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting with mixtures. Outlining useful techniques through an applied approach with examples from real research situations, the book supplies a comprehensive discussion of how to design and set up basic mixture experiments, then analyze the data and draw inferences from results. Drawing from his extensive experience teaching the topic at various levels, the author presents the mixture experiments in an easy-to-follow manner that is void of unnecessary formulas and theory. Succinct presentations explore key methods and techniques for carrying out basic mixture experiments, including: Designs and models for exploring the entire simplex factor space, with coverage of simplex-lattice and simplex-centroid designs, canonical polynomials, the plotting of individual residuals, and axial designs Multiple constraints on the component proportions in the form of lower and/or upper bounds, introducing L-Pseudocomponents, multicomponent constraints, and multiple lattice designs for major and minor component classifications Techniques for analyzing mixture data such as model reduction and screening components, as well as additional topics such as measuring the leverage of certain design points Models containing ratios of the components, Cox's mixture polynomials, and the fitting of a slack variable model A review of least squares and the analysis of variance for fitting data Each chapter concludes with a summary and appendices with details on the technical aspects of the material. Throughout the book, exercise sets with selected answers allow readers to test their comprehension of the material, and References and Recommended Reading sections outline further resources for study of the presented topics. A Primer on Experiments with Mixtures is an excellent book for one-semester courses on mixture designs and can also serve as a supplement for design of experiments courses at the upper-undergraduate and graduate levels. It is also a suitable reference for practitioners and researchers who have an interest in experiments with mixtures and would like to learn more about the related mixture designs and models.

Wittgenstein’s Beetle and Other Classic Thought Experiments invites readers to participate actively in discovering the surprisingly powerful and fruitful tradition of «thought experiments.» Gives a lively presentation of an «A to Z» of 26 fascinating and influential thought experiments from philosophy and science Presents vivid and often humorous discussion of the experiments, including strengths and weaknesses, historical context, and contemporary uses Provides a «how to» section for engaging in thought experiments Includes illustrations, mini-biographies, and suggestions for further reading.